Numerous advances have improved our ability to collect valid and reliable data on health behaviors and outcomes. However, health behaviors are often influenced by psychosocial variables - such as attitudes and beliefs - that are unobservable and, thus, more difficult to measure. Attitudes and beliefs are typically measured using Likert-scaled items, in which respondents rate their agreement with statements along a continuum. Since the 1920s, researchers have observed that some respondents tend to systematically agree to Likert-scaled questionnaire items, regardless of question content. This pattern of responding to survey questions is known as acquiescent response style (ARS). ARS jeopardizes efforts to reduce health disparities. ARS can weaken health experts' understanding of what factors influence health behaviors, their ability to create effective interventions, and th accuracy with which they evaluate programs to reduce health disparities. Research indicates that ARS use may be influenced by culture, and, in the U.S., may be of particular concern when surveying Latino populations. Research by the investigators and others suggests that 22-24 percent of Latino survey respondents acquiesce on health surveys, as compared to 13 percent of non-Latino Whites. These culturally patterned differences in ARS may introduce error in health survey data, which, in turn, may artificially create or enhance distinctions both within Latino populations and between Latinos and non-Latino Whites, thereby erroneously informing health disparities research. The Latino population is demographically and culturally diverse, and almost nothing is known about what factors may drive ARS use among Latinos from different ethnic or cultural groups. Further, despite a growing need to obtain valid health data from Latinos, who comprise 16 percent of the U.S. population and are expected to increase to 29 percent by 2050, it is unclear how to address ARS. The proposed study will: (1) identify predictors of ARS; and (2) screen for the most promising methods of reducing ARS during data collection and adjusting for ARS after data collection is complete. This research focuses on Mexican Americans, Puerto Ricans, and Cuban Americans, as these groups comprise the three largest Latino sub-groups. Data from this study will be derived from two surveys. The first survey will gather data from 2900 Mexican Americans, Puerto Ricans, Cuban Americans, and non-Latino Whites in order to identify factors associated with ARS. The second survey will compare different methods of addressing ARS among 1161 Mexican American, Puerto Rican, and Cuban American health survey respondents. Findings from this research will provide researchers with empirically driven guidance on when to anticipate and how to reduce ARS-associated measurement error when surveying Latino respondents. Such knowledge will improve health data validity through increased ARS awareness and standardization of methods to address ARS, thereby contributing to more accurate understanding of the psychosocial determinants of Latino health, more effective health promotion programs targeting Latinos, and better long-term Latino health outcomes.